Predicting community responses to perturbations in the face of imperfect knowledge and network complexity

How best to predict the effects of perturbations to ecological communities has been a long-standing goal for both applied and basic ecology. This quest has recently been revived by new empirical data, new analysis methods, and increased computing speed, with the promise that ecologically important insights may be obtainable from a limited knowledge of community interactions. We use empirically based and simulated networks of varying size and connectance to assess two limitations to predicting perturbation responses in multispecies communities: (1) the inaccuracy by which species interaction strengths are empirically quantified and (2) the indeterminacy of species responses due to indirect effects associated with network size and structure. We find that even modest levels of species richness and connectance (similar to 25 pairwise interactions) impose high requirements for interaction strength estimates because system indeterminacy rapidly overwhelms predictive insights. Nevertheless, even poorly estimated interaction strengths provide greater average predictive certainty than an approach that uses only the sign of each interaction. Our simulations provide guidance in dealing with the trade-offs involved in maximizing the utility of network approaches for predicting dynamics in multispecies communities.

Scaling of Food-Web Properties with Diversity and Complexity Across Ecosystems

Trophic scaling models describe how topological food-web properties such as the number of predator prey links scale with species richness of the community. Early models predicted that either the link density (i.e. the number of links per species) or the connectance (i.e. the linkage probability between any pair of species) is constant across communities. More recent analyses, however, suggest that both these scaling models have to be rejected, and we discuss several hypotheses that aim to explain the scale dependence of these complexity parameters. Based on a recent, highly resolved food-web compilation, we analysed the scaling behaviour of 16 topological parameters and found significant power law scaling relationships with diversity (i.e. species richness) and complexity (i.e. connectance) for most of them. These results illustrate the lack of universal constants in food-web ecology as a function of diversity or complexity. Nonetheless, our power law scaling relationships suggest that fundamental processes determine food-web topology, and subsequent analyses demonstrated that ecosystem-specific differences in these relationships were of minor importance. As such, these newly described scaling relationships provide robust and testable cornerstones for future structural food-web models.

ON THE MOLECULAR COMPLEXITY OF THE HOT CORES IN ORION-A - GRAIN SURFACE-CHEMISTRY AS THE LAST REFUGE OF THE SCOUNDREL

We have modeled the gas phase chemistry of warm molecular material around protostars that is seeded with evaporating grain mantles. We show that the release of simple molecules into the gas drives ion-molecule and neutral chemistries which can account for many of the complex 0-bearing and N-bearing molecules observed in hot cores. Initial grain mantle components and secondary product molecules are identified, and the observational consequences are discussed.

A Low Complexity Real-time MIMO-Preprocessing For Fixed Complexity Sphere Decoder

Modern Multiple-Input Multiple-Output (MIMO) communication systems place huge demands on embedded processing resources in terms of throughput, latency and resource utilization. State-of-the-art MIMO detector algorithms, such as Fixed-Complexity Sphere Decoding (FSD), rely on efficient channel preprocessing involving numerous calculations of the pseudo-inverse of the channel matrix by QR Decomposition (QRD) and ordering. These highly complicated operations can quickly become the critical prerequisite for real-time MIMO detection, exaggerated as the number of antennas in a MIMO detector increases. This paper describes a sorted QR decomposition (SQRD) algorithm extended for FSD, which significantly reduces the complexity and latency
of this preprocessing step and increases the throughput of MIMO detection. It merges the calculations of the QRD and ordering operations to avoid multiple iterations of QRD. Specifically, it shows that SQRD reduces the computational complexity by over 60-70% when compared to conventional
MIMO preprocessing algorithms. In 4x4 to 7x7 MIMO cases, the approach suffers merely 0.16-0.2 dB reduction in Bit Error Rate (BER) performance.

Fabrication and Ms Conduct: Scrutinising Practice Through Feminist Theory

This paper describes a collaborative practice, between an architect (the author) and a textile designer; its outcomes and the critical theoretical and feminist contexts from which the practice evolved and to which it still responds. The practice advocates the interweaving of more than the yarns, material and cultures on which it is physically based, but also the intertwining of theory and technology as a means to advance architectural practice. This is done in response to Ahrentzen’s charge to feminist scholars and practitioners to ‘embrace not only the abstract conceptual nature of much postmodernist theorizing but also that derived from the serious “hanging out”, looking at, listening to, scrutinising and theorizing lived experiences of the everyday’, in this instance the everyday practice of combining concrete and textiles.

Evidence for complexity at the nanometer scale of radiation-induced DNA DSBs as a determinant of rejoining kinetics

The rejoining kinetics of double-stranded DNA fragments, along with measurements of residual damage after postirradiation incubation, are often used as indicators of the biological relevance of the damage induced by ionizing radiation of different qualities. Although it is widely accepted that high-LET radiation-induced double-strand breaks (DSBs) tend to rejoin with kinetics slower than low-LET radiation-induced DSBs, possibly due to the complexity of the DSB itself, the nature of a slowly rejoining DSB-containing DNA lesion remains unknown. Using an approach that combines pulsed-field gel electrophoresis (PFGE) of fragmented DNA from human skin fibroblasts and a recently developed Monte Carlo simulation of radiation-induced DNA breakage and rejoining kinetics, we have tested the role of DSB-containing DNA lesions in the 8-kbp-5.7-Mbp fragment size range in determining the DSB rejoining kinetics. It is found that with low-LET X rays or high LET alpha particles, DSB rejoining kinetics data obtained with PFGE can be computer-simulated assuming that DSB rejoining kinetics does not depend on spacing of breaks along the chromosomes. After analysis of DNA fragmentation profiles, the rejoining kinetics of X-ray-induced DSBs could be fitted by two components: a fast component with a half-life of 0.9 +/- 0.5 h and a slow component with a half-life of 16 +/- 9 h. For a particles, a fast component with a half-life of 0.7 +/- 0.4 h and a slow component with a half-life of 12 5 h along with a residual fraction of unrepaired breaks accounting for 8% of the initial damage were observed. In summary, it is shown that genomic proximity of breaks along a chromosome does not determine the rejoining kinetics, so the slowly rejoining breaks induced with higher frequencies after exposure to high-LET radiation (0.37 +/- 0.12) relative to low-LET radiation (0.22 +/- 0.07) can be explained on the basis of lesion complexity at the nanometer scale, known as locally multiply damaged sites. (c) 2005 by Radiation Research Society.

How Organizations Engage with External Complexity: A Political Action Perspective

This paper offers a new insight into how organizations engage with external complexity. It applies a political action perspective that draws attention to the hitherto neglected question of how the relative power organizational leaders enjoy within their environments is significant for the actions they can take on behalf of their organizations when faced with external complexity. It identifies cognitive and relational complexity as two dimensions of the environment with which organizations have to engage. It proposes three modes whereby organizations may engage with environmental complexity that are conditioned by an organization's power within its environment. It also considers the intention associated with each mode, as well as the implications of these modes of engagement for how an organization can learn about its environment and for the use of rationality and intuition in its strategic decision-making. The closing discussion considers how this analysis integrates complexity and political action perspectives in a way that contributes to theoretical development and provides the basis for a dynamic political co-evolutionary approach. © The Author(s) 2011.

Conundrums in Conservation: Complexity in Control

The departure point for this investigation is to highlight the centrality of regulation theory as a praxis in planning enforcement. The value of the conceptual framework is demonstrated by application in the problematic arena of conservation regulatory compliance, where there is currently a dearth of investigation. It is evidenced that this thematic approach provides a lens to scrutinise problematic areas of control and provides a deeper understanding of the difficulties faced by planning enforcement operational practice generally and heritage regimes specifically. The utility of the proposed mechanism is that it remedies the current well documented pitfalls of disjointed, piecemeal strategies by providing a framework for robust, coherent decision making not only in planning but in the wider regulatory arena.

Functional responses of the intertidal amphipod Echinogammarus marinus: effects of prey supply, model selection and habitat complexity.

The influence of predation in structuring ecological communities can be informed by examining the shape and magnitude of the functional response of predators towards prey. We derived functional responses of the ubiquitous intertidal amphipod Echinogammarus marinus towards one of its preferred prey species, the isopod Jaera nordmanni. First, we examined the form of the functional response where prey were replaced following consumption, as compared to the usual experimental design where prey density in each replicate is allowed to deplete. E. marinus exhibited Type II functional responses, i.e. inversely density-dependent predation of J. nordmanni that increased linearly with prey availability at low densities, but decreased with further prey supply. In both prey replacement and non-replacement experiments, handling times and maximum feeding rates were similar. The non-replacement design underestimated attack rates compared to when prey were replaced. We then compared the use of Holling’s disc equation (assuming constant prey density) with the more appropriate Rogers’ random predator equation (accounting for prey depletion) using the prey non-replacement data. Rogers’ equation returned significantly greater attack rates but lower maximum feeding rates, indicating that model choice has significant implications for parameter estimates. We then manipulated habitat complexity and found significantly reduced predation by the amphipod in complex as opposed to simple habitat structure. Further, the functional response changed from a Type II in simple habitats to a sigmoidal, density-dependent Type III response in complex habitats, which may impart stability on the predator−prey interaction. Enhanced habitat complexity returned significantly lower attack rates, higher handling times and lower maximum feeding rates. These findings illustrate the sensitivity of the functional response to variations in prey supply, model selection and habitat complexity and, further, that E. marinus could potentially determine the local exclusion and persistence of prey through habitat-mediated changes in its predatory functional responses.

Exploring statistical and population aspects of network complexity

The characterization and the definition of the complexity of objects is an important but very difficult problem that attracted much interest in many different fields. In this paper we introduce a new measure, called network diversity score (NDS), which allows us to quantify structural properties of networks. We demonstrate numerically that our diversity score is capable of distinguishing ordered, random and complex networks from each other and, hence, allowing us to categorize networks with respect to their structural complexity. We study 16 additional network complexity measures and find that none of these measures has similar good categorization capabilities. In contrast to many other measures suggested so far aiming for a characterization of the structural complexity of networks, our score is different for a variety of reasons. First, our score is multiplicatively composed of four individual scores, each assessing different structural properties of a network. That means our composite score reflects the structural diversity of a network. Second, our score is defined for a population of networks instead of individual networks. We will show that this removes an unwanted ambiguity, inherently present in measures that are based on single networks. In order to apply our measure practically, we provide a statistical estimator for the diversity score, which is based on a finite number of samples.